Senior Machine Learning Engineer (Large Systems) New London, UK
Senior Machine Learning Engineer (Large Systems) New London, UK

Senior Machine Learning Engineer (Large Systems) New London, UK

Full-Time 48000 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Develop and optimise AI models for cutting-edge hardware in a dynamic environment.
  • Company: Join Graphcore, a leader in AI compute backed by SoftBank Group.
  • Benefits: Enjoy flexible working, generous leave, private medical insurance, and more.
  • Why this job: Make a tangible impact on the future of AI technology with innovative projects.
  • Qualifications: Strong skills in machine learning, Python/C++, and experience with large-scale systems.
  • Other info: Collaborate with top minds in AI and contribute to groundbreaking advancements.

The predicted salary is between 48000 - 72000 £ per year.

About Graphcore

At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacentre scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world. We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary

As a Senior Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation at scale, eager to make a tangible impact in this rapidly evolving field.

The Team

The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. We build reference applications, contribute to key software libraries e.g. optimising kernels for efficiency on our hardware, and collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications.

Responsibilities

  • Implement latest machine learning models and optimise them for performance and accuracy, scaling to 1000s of accelerators.
  • Test and evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews.
  • Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency.
  • Design and conduct experiments on novel AI methods, implement them and evaluate results.
  • Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
  • Engage with AI community and keep in touch with the latest developments in AI.

Qualifications

  • Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field.
  • Proficiency in deep learning frameworks like PyTorch/JAX.
  • Strong Python or C++ software development skills.
  • Expertise in deep learning from model training to optimisation and evaluation.
  • Experience in distributed training or inference of ML models across 64+ accelerators.
  • Capable of designing, executing and reporting from ML experiments.
  • Developed deep understanding of performance bottlenecks and how to overcome them.
  • Ability to move quickly in a dynamic environment.
  • Enjoy cross-functional work collaborating with other teams.
  • Strong communicator - able to explain complex technical concepts to different audiences.
  • Experience in one or more of: MLOps for Kubernetes-based clusters, Building production systems with large language models, Efficient computing based on low-precision arithmetic.
  • Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models.
  • Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies.
  • Have contributed to open-source projects or published research papers in relevant fields.
  • Knowledge of cloud computing platforms.
  • Keen to present, publish and deliver talks in the AI community.

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments. Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications.

Senior Machine Learning Engineer (Large Systems) New London, UK employer: graphcore

Graphcore is an exceptional employer, offering a dynamic work environment in the heart of New London where innovation thrives. With a strong commitment to employee growth, we provide opportunities for collaboration across teams and access to cutting-edge technology, all while promoting a culture of inclusivity and well-being through generous benefits like flexible working, comprehensive health plans, and a supportive parental leave policy. Join us to make a meaningful impact in the rapidly evolving field of AI, surrounded by some of the brightest minds in the industry.
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Contact Detail:

graphcore Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Senior Machine Learning Engineer (Large Systems) New London, UK

✨Tip Number 1

Network like a pro! Reach out to current employees at Graphcore on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for your application process. Personal connections can make a huge difference!

✨Tip Number 2

Prepare for technical interviews by brushing up on your machine learning concepts and coding skills. Practice solving problems on platforms like LeetCode or HackerRank. The more comfortable you are with the tech, the better you'll perform!

✨Tip Number 3

Showcase your passion for AI! Be ready to discuss recent advancements in the field and how they relate to Graphcore's work. This will demonstrate your enthusiasm and commitment to contributing to their innovative projects.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Graphcore team!

We think you need these skills to ace Senior Machine Learning Engineer (Large Systems) New London, UK

Machine Learning
Deep Learning Frameworks (PyTorch, JAX)
Python
C++
Model Training and Optimisation
Distributed Training and Inference
Performance Benchmarking
Experiment Design and Evaluation
MLOps for Kubernetes
Production Systems with Large Language Models
CUDA Kernels for Performance Optimisation
HPC Systems and Networking (Infiniband, NVLink, RoCE)
Cloud Computing Platforms
Strong Communication Skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Machine Learning Engineer role. Highlight your expertise in deep learning frameworks and any relevant projects you've worked on, especially those involving large-scale systems.

Craft a Compelling Cover Letter: Use your cover letter to tell us why you're excited about working at Graphcore. Share specific examples of how your background in AI and machine learning can contribute to our mission of advancing AI technology.

Showcase Your Projects: If you've contributed to open-source projects or published research papers, make sure to mention them! This shows us your commitment to the AI community and your ability to innovate in the field.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do!

How to prepare for a job interview at graphcore

✨Know Your Tech Inside Out

Make sure you’re well-versed in the latest machine learning models and frameworks like PyTorch or JAX. Brush up on your Python or C++ skills, as you'll likely be asked to demonstrate your technical expertise during the interview.

✨Showcase Your Problem-Solving Skills

Prepare to discuss specific examples where you've identified performance bottlenecks and how you overcame them. Graphcore values innovation, so think of ways you can contribute to optimising AI models for their specialised hardware.

✨Collaborate and Communicate

Since the role involves working closely with various teams, practice explaining complex technical concepts in simple terms. Be ready to share experiences where you’ve successfully collaborated across functions, as this will highlight your teamwork skills.

✨Stay Updated on AI Trends

Engage with the AI community and keep abreast of the latest developments. Mention any relevant open-source contributions or research papers you’ve worked on, as this shows your passion for the field and commitment to continuous learning.

Senior Machine Learning Engineer (Large Systems) New London, UK
graphcore

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